specific steps in data modeling (1) conceptualize the user's view of data –what are the basic...

Specific Steps in Data Modeling(1) Conceptualize the user's view of data

– what are the basic features needed to solve the problem?

(2) Select the geographic representation – points, lines, areas, rasters, TINs

(3) Define objects, features, and relationships – draw a UML diagram, specify relationships,

“behaviors”

(4) Match to geodatabase elements– Refine relationships, “behaviors”

(5) Organize geodatabase structure, add data

( 1 ) User’s View of Data

( 1 ) User’s View of Data cont.

(2)Select

geographic rep.

Steps in Data Modeling(1) Conceptualize the user's view of data

– what are the basic features needed to solve the problem?

(2) Select the geographic representation – points, lines, areas, rasters, TINs

(3) Define objects and relationships – draw a UML diagram, specify relationships,

“behaviors”

(4) Match to geodatabase elements– Refine relationships, “behaviors”

(5) Organize geodatabase structure, add data

Unified Modeling Language• Entity-relationship diagrams

• Design methodologies, diagram notations

• UML– Not a design methodology

– Just a diagrammatic notation based on methods

– Endorsed by leading software and database companies

• HTML

Unified Modeling LanguageUML

• Diagrammatic notation = “visual language”...

• For constructing a data model– Explains, documents on object-oriented structure

• Drawings, relationships constructed in Visio– Like CAD for Civil Engineering

• Tools to input a drawing to ArcGIS– input data to the data model

Basic UML Grammer

• Things– “Classes” sometimes grouped in “Packages”

• Relationships

• Diagrams

UML Things

UML NotationZeiler pp. 97-99

• a class is shown as a box

• top part contains the name of the class

• lower part contains the attributes

• methods associated with the class

• lines connect boxes and indicate relationships

UML Notation ( cont. )

• Abstract class – specify subclasses

underneath– Mammals w/human or

dog feature classes– no new instances

• Feature Class– Specify subtypes

underneath– Human, dog, cat

Example: Chicken Object Model

Graphic courtesy of Maidment et al., ArcHydro team

Objects and Features

• Object (real world)– in ArcGIS an object is non-spatial

– it is NOT a point, line, or area

– it has no geographic location

– it has no shape attribute in its table

– Drainage network, ship, vehicle, … customer, lake, house, etc.

• Feature (spatial context)– an object that has geographic location

– a point, line, area, TIN, raster

Relationships

• Links between classes, shown as lines

• One to one

• One to many

• Many to many

Relationships (cont.)

• 1:1 - solid line– one record in Class A linked to one record in

Class B• “is married to”• the class of state capitals linked to the class of

states

• 1:n - solid line with * at one end– one record in Class A linked to any number of

records in Class B• "owns" • the class of states linked to the class of area codes

Relationships (cont.)

• m:n - solid line with * at both ends– any number of records in Class A linked to any

number of records in Class B• "has visited”• "was never married to" • the class of mountain lions linked to the class of

wilderness areas

Graphic courtesy of Maidment et al., ArcHydro team

Type Inheritance

• White triangle• Class B inherits the

properties (attributes, methods) of Class A

• the class street inherits from the class transportation network

• Solid diamond• the parts and the whole

depend on each other

Graphic courtesy of Maidment et al., ArcHydro team

MDeviceIDEastNorthSpeedDirection112.110.88.6121111.312.57.922019.3-3.57.5130114.015.13.923417.312.09.1115

MeasuredData

InstantaneousPoint (ex: CTD)InstantaneousPoint (ex: CTD)

Measurement

XX

YY

TimeStampTimeStamp

MeasuringDevice

MDeviceIDNameTypeMeasurementID1Bob12Poncho13Juanita14Mia25Anita2

MeasuringDevice

MTypeIDVarNameVarDesc VarUnitsMDeviceID1Oranges12Bananas13Cubic cm24Rocks25Limes3MeasuredType

ZZ

MarineIDMarineCodeSeriesIDIPointTypeRecordedTime1AAA1105/04/58 12:00 002BBB1105/04/58 12:30 003CCC1105/04/58 13:00 00

InstantaneousPoints

MeasurementMeasureIDMarineIDZLocXlocYlocServiceTripSeviceDesc11-0.821-1.531-3.542-0.852-1.5

Michael Blongewicz

ArcMarine GeodatabaseOverall Geodatabase

Feature Class

Feature ClassFeature Dataset

Table

RelationshipClass

Steps in Data Modeling(1) Conceptualize the user's view of data

– what are the basic features needed to solve the problem?

(2) Select the geographic representation – points, lines, areas, rasters, TINs

(3) Define objects and relationships – draw a UML diagram, specify relationships,

“behaviors”

(4) Match to geodatabase elements– Refine relationships, “behaviors”

(5) Organize geodatabase structure, add data

Data Model Levels

IncreasingAbstraction

RealityReality

Conceptual ModelConceptual Model

Logical ModelLogical Model

Physical ModelPhysical Model

Human-oriented

Computer-oriented

Real World Objects and relationships

DatabaseSchema

(Object state)

Physical Model

Modeling ProcessConceptual Model

Lists, flow diagrams, etc

Logical ModelDiagram in CASE

Tool

Graphic courtesy of ESRI

Steps in Data Modeling(1) Conceptualize the user's view of data

– what are the basic features needed to solve the problem?

(2) Select the geographic representation – points, lines, areas, rasters, TINs

(3) Define objects and relationships – draw a UML diagram, specify relationships,

“behaviors”

(4) Match to geodatabase elements– Refine relationships, “behaviors”

(5) Organize geodatabase structure, add data– e.g., Marine Data Model tutorial

Arc Marine Data Model Exercise

• Exercise and data at dusk.geo.orst.edu/djl/arcgis/ArcMarine_Tutorial/

• What to turn in:– Screen snapshot of what your ArcMap session looks like

at the end of Section 4 (including dynseg referencing)

– Answers to 2 simple questions at end of Section 4 (which cruise? which vehicle?)

– Can put all of the above in a single MS-Word document, labeled with your NAME please!

• Due in Dropbox, May 3rd, 6:00 p.m.

Gateway to the Literature• Arctur, D. and Zeiler, M., 2004, Designing Geodatabases, ESRI

Press• Lowe, J.W., 2003. Flexible data models strut the runway.

Geospatial Solutions, 13(2): 44-47.• Maidment, D.R., 2002. Arc Hydro: GIS for Water Resources,

ESRI Press, 203 pp. w/CD.• Li, X. and M.E. Hodgson, 2004. Vector field data model and

operations. GISci. Rem. Sens., 41(1): 1-24.• Wright, D., Blongewicz, M., Halpin, P., and Breman, J., A new

object-oriented data model for coasts, seas, and lakes, in Green, D.R. (ed.), Coastal and Marine Geospatial Technologies, London: Springer, in press. – dusk.geo.orst.edu/djl/arcgis/coastgis_book_final.pdf

• Wright, D.J., Halpin, P.N., Blongewicz, M.J., and Breman, J.B., Arc Marine: GIS for a Blue Planet, Redlands, CA: ESRI Press, in prep and review, due out 2006/7. – dusk.geo.orst.edu/djl/arcgis/book

Resulting Analysis - ArcHydro

From Arctur and Zeiler, Geodatabase Design, ESRI Press.